DBMS > EventStoreDB vs. Informix vs. KairosDB vs. Lovefield vs. OrigoDB

System Properties Comparison EventStoreDB vs. Informix vs. KairosDB vs. Lovefield vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

A fully ACID in-memory object graph database

Primary database model

Event Store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.eventstore.com

www.ibm.com/products/informix

github.com/kairosdb/kairosdb

google.github.io/lovefield

origodb.com

Technical documentation

developers.eventstore.com

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

kairosdb.github.io

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

Developer

Event Store Limited

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Google

Robert Friberg et al

Initial release

2012

1984

2013

2014

2009

under the name LiveDB

Current release

21.2, February 2021

14.10.FC5, November 2020

1.2.2, November 2018

2.1.12, February 2017

License

Commercial or Open Source

Open Source

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and Java

Java

JavaScript

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

User defined using .NET types and collections

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

JavaScript

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

Users with fine-grained authentication, authorization, and auditing controls

simple password-based access control

Role based authorization

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